Senior Computer Vision Engineer

Senior Computer Vision Engineer

• Location: Coimbatore
• Work Mode: Onsite
• Experience: 3 5 Years

We are looking for a Senior Computer Vision Engineer with hands-on experience in designing developing and deploying computer vision solutions using deep learning. The role involves working on image and video processing pipelines real-time systems and scalable deployment environments. The candidate will collaborate with cross-functional teams to build and integrate production-grade vision systems.

• Design and develop computer vision models for image and video-based applications
• Implement deep learning models for object detection segmentation tracking and feature extraction
• Build and optimize end-to-end CV pipelines for real-time and batch processing
• Deploy CV models in on-premises environments and ensure system reliability
• Work with high-volume video streams and implement real-time processing solutions
• Integrate CV systems with existing infrastructure databases and enterprise systems
• Perform model optimization including compression and quantization
• Develop scalable solutions using containerization and orchestration tools
• Implement load balancing and scaling strategies across distributed systems
• Collaborate with MLOps teams for model versioning experiment tracking and CI/CD pipelines
• Ensure adherence to security best practices for model and data protection
• Support debugging performance tuning and production monitoring

• Bachelors or Masters degree in Computer Science Electronics Electrical Engineering or related field
• 3 5 years of experience in computer vision and deep learning-based solutions
• Strong foundation in machine learning deep learning and image processing concepts
• Experience in deploying production-grade CV systems

Programming & Frameworks:

• Python C
• PyTorch TensorFlow Keras

Computer Vision & Deep Learning:

• CNNs RNNs GANs
• Object Detection Image Segmentation Tracking
• Feature Extraction and Image Processing

Libraries & Tools:

• OpenCV scikit-image PIL/Pillow
• Data Annotation Tools: LabelImg CVAT RectLabel

Systems & Deployment:

• On-premises deployment of CV models
• Real-time streaming (Kafka or similar)
• Distributed systems and scaling

DevOps & MLOps:

• Git GitHub GitLab
• Docker Kubernetes
• Model versioning experiment tracking CI/CD

Optimization Techniques:

• Model compression
• Quantization

Infrastructure & Integration:

• Integration with enterprise systems and databases
• Load balancing and multi-machine scaling

Security:

• Secure deployment practices for CV models and data

• Experience with hybrid cloud platforms (AWS Azure Google Cloud)
• Exposure to edge devices (NVIDIA Jetson Intel NUC embedded systems)
• Experience in high-throughput streaming systems (Kafka)
• Knowledge of distributed computing and large-scale CV systems
  
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